Campaigns Sequence Writing

---
name: campaigns-sequence-writing
description: Draft and revise complete Clay Sequencer email sequences using supplied campaign strategy and context.
---

# Clay Sequencer sequence writing

If the `campaigns` skill is not already loaded, load it before acting. Use it for campaign discovery, context, target selection, commands, and mutation boundaries. Use this skill for sequence-writing decisions.

Use this skill to draft a complete email sequence or revise sequence copy. Treat the supplied campaign strategy and context as the source of truth.

## Message strategy

Establish the intended recipient and the situation that makes the message relevant. Connect that situation to a specific problem or opportunity, explain the mechanism and value offered, and make the offer and requested response clear.

Give each email one primary purpose and one response path. When a draft is not working, fix the strategy before polishing individual lines. Omit proof that the supplied context does not support. Make every follow-up add a distinct reason to respond rather than restating an earlier message.

## Copy execution

- Use direct language with concrete actors and outcomes.
- Give each sentence one purpose.
- Ground relevance in supplied facts and context rather than generic personalization.
- Remove filler and redundant restatement.
- Choose tone and punctuation for the recipient, situation, and established voice.
- Preserve copy outside the requested revision scope.

## Dynamic copy

- When the language is shared across the audience, use fixed copy.
- When only one known value changes, use a direct lead-field token.
- When bounded lexical variation does not depend on lead facts, use spintax.
- Do not discard useful, supported lead data only because some leads lack it. When worthwhile variation must select, combine, or interpret that data into natural prose, use a short, bounded AI snippet. Do not let missing data produce unsupported copy.
- When meaningful per-lead variation can improve relevance and impact, use it. Treat its support for deliverability as possible, not guaranteed.
- Never use an AI snippet as unfinished fixed copy or for generic variation. Never add one only to clear a personalization warning or meet a quota.
- Give each snippet one role, explicit evidence, and an output bound.
- Prioritize grounding over variation.